On the public citation graph
Fragment-Based de Novo Ligand Design by Multiobjective Evolutionary Optimization
0 signed · 192 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/(sici)1097-0134(19991001)37:1<88::aid-prot9>3.0.co;2-oopenalex-snapshot
Exhaustive docking of molecular fragments with electrostatic solvation
inferredcites →https://doi.org/10.1002/1521-3773(20001117)39:22<4133::aid-anie4133>3.0.co;2-xopenalex-snapshot
Chirally Modifiedn-Butyllithium: Tuning the Composition, Structure, and Enantioselectivity with Modular Fencholates
inferredcites →https://doi.org/10.1002/jcc.540040211openalex-snapshot
CHARMM : A program for macromolecular energy, minimization, and dynamics calculations
inferredcites →https://doi.org/10.1002/jcc.540130714openalex-snapshot
Validation of the general purpose QUANTA ®3.2/CHARMm® force field
inferredcites →https://doi.org/10.1002/med.1021openalex-snapshot
Cyclin‐dependent kinase inhibitors for treating cancer
inferredcites →https://doi.org/10.1002/qsar.200410012openalex-snapshot
Identification of novel cannabinoid receptor ligands via evolutionary de novo design and rapid parallel synthesis
inferredcites →https://doi.org/10.1007/bf00124471openalex-snapshot
Computational combinatorial ligand design: Application to human ?-thrombin
inferredcites →https://doi.org/10.1007/bf02174466openalex-snapshot
SPROUT, HIPPO and CAESA: Tools for de novo structure generation and estimation of synthetic accessibility
inferredcites →https://doi.org/10.1007/s0089400060498openalex-snapshot
LigBuilder: A Multi-Purpose Program for Structure-Based Drug Design
inferredcites →https://doi.org/10.1016/0305-0548(86)90048-1openalex-snapshot
Future paths for integer programming and links to artificial intelligence
inferredcites →https://doi.org/10.1016/0898-5529(90)90162-2openalex-snapshot
An alternative method for the alignment of molecular structures: Maximizing electrostatic and steric overlap
inferredcites →https://doi.org/10.1016/j.bmcl.2005.10.038openalex-snapshot
Computer-aided design of non-nucleoside inhibitors of HIV-1 reverse transcriptase
inferredcites →https://doi.org/10.1016/s0010-4655(98)00016-2openalex-snapshot
Continuum solvation model: Computation of electrostatic forces from numerical solutions to the Poisson-Boltzmann equation
inferredcites →https://doi.org/10.1016/s0169-409x(00)00129-0openalex-snapshot
Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings 1PII of original article: S0169-409X(96)00423-1. The article was originally published in Advanced Drug Delivery Reviews 23 (1997) 3–25. 1
inferredcites →https://doi.org/10.1016/s0169-409x(96)00423-1openalex-snapshot
Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings
inferredcites →https://doi.org/10.1021/ci0255782openalex-snapshot
Cheminformatics Analysis of Organic Substituents: Identification of the Most Common Substituents, Calculation of Substituent Properties, and Automatic Identification of Drug-like Bioisosteric Groups
inferredcites →https://doi.org/10.1021/ci049714+openalex-snapshot
ZINC − A Free Database of Commercially Available Compounds for Virtual Screening
inferredcites →https://doi.org/10.1021/ci0502956openalex-snapshot
Generation and Selection of Novel Estrogen Receptor Ligands Using the De Novo Structure-Based Design Tool, SkelGen
inferredcites →https://doi.org/10.1021/ci050338iopenalex-snapshot
Exhaustive de novo Design of Low-Molecular-Weight Fragments Against the ATP-Binding Site of DNA-Gyrase
inferredcites →https://doi.org/10.1021/ci6005307openalex-snapshot
Flux (2): Comparison of Molecular Mutation and Crossover Operators for Ligand-Based de Novo Design
inferredcites →https://doi.org/10.1021/ci970429iopenalex-snapshot
RECAPRetrosynthetic Combinatorial Analysis Procedure: A Powerful New Technique for Identifying Privileged Molecular Fragments with Useful Applications in Combinatorial Chemistry
inferredcites →https://doi.org/10.1021/cr00023a012openalex-snapshot
From atoms and bonds to three-dimensional atomic coordinates: automatic model builders
inferredcites →https://doi.org/10.1021/j100374a066openalex-snapshot
Determination of net atomic charges using a modified partial equalization of orbital electronegativity method. 1. Application to neutral molecules as models for polypeptides
inferredcites →https://doi.org/10.1021/ja963689+openalex-snapshot
SMoG: de Novo Design Method Based on Simple, Fast, and Accurate Free Energy Estimates. 2. Case Studies in Molecular Design
inferredcites →https://doi.org/10.1021/jm00064a003openalex-snapshot
GroupBuild: a fragment-based method for de novo drug design
inferredcites →https://doi.org/10.1021/jm010117dopenalex-snapshot
Oxindole-Based Inhibitors of Cyclin-Dependent Kinase 2 (CDK2): Design, Synthesis, Enzymatic Activities, and X-ray Crystallographic Analysis
inferredcites →https://doi.org/10.1021/jm020056zopenalex-snapshot
Probing the ATP Ribose-Binding Domain of Cyclin-Dependent Kinases 1 and 2 withO6-Substituted Guanine Derivatives
inferredcites →https://doi.org/10.1021/jm030809xopenalex-snapshot
SYNOPSIS: SYNthesize and OPtimize System in Silico
inferredcites →https://doi.org/10.1021/jm0492296openalex-snapshot
LEA3D: A Computer-Aided Ligand Design for Structure-Based Drug Design
inferredcites →https://doi.org/10.1021/jm049726mopenalex-snapshot
Efficient Evaluation of Binding Free Energy Using Continuum Electrostatics Solvation
inferredcites →https://doi.org/10.1021/jm060838iopenalex-snapshot
Automatic and Efficient Decomposition of Two-Dimensional Structures of Small Molecules for Fragment-Based High-Throughput Docking
inferredcites →https://doi.org/10.1021/jm070654jopenalex-snapshot
Discovery of Kinase Inhibitors by High-Throughput Docking and Scoring Based on a Transferable Linear Interaction Energy Model
inferredcites →https://doi.org/10.1021/jm9602928openalex-snapshot
The Properties of Known Drugs. 1. Molecular Frameworks
inferredcites →https://doi.org/10.1021/jm9903996openalex-snapshot
Properties of Known Drugs. 2. Side Chains
inferredcites →https://doi.org/10.1023/a:1008040531766openalex-snapshot
Combinatorial docking and combinatorial chemistry: Design of potent non-peptide thrombin inhibitors
inferredcites →https://doi.org/10.1023/a:1008042711516openalex-snapshot
Evaluation of a method for controlling molecular scaffold diversity in de novo ligand design
inferredcites →https://doi.org/10.1023/a:1008184403558openalex-snapshot
De novo design of molecular architectures by evolutionary assembly of drug-derived building blocks
inferredcites →https://doi.org/10.1023/a:1014389729000openalex-snapshot
A genetic algorithm for structure-based de novo design
inferredcites →https://doi.org/10.1038/nrd1799openalex-snapshot
Computer-based de novo design of drug-like molecules
inferredcites →https://doi.org/10.1063/1.1699114openalex-snapshot
Equation of State Calculations by Fast Computing Machines
inferredcites →https://doi.org/10.1201/9780367802486openalex-snapshot
Handbook of Evolutionary Computation
inferredcites →https://doi.org/10.1515/bc.2001.168openalex-snapshot
Fragment-Based Flexible Ligand Docking by Evolutionary Optimization
inferredcites →https://doi.org/10.2174/092986706778521797openalex-snapshot
Docking and Scoring - Theoretically Easy, Practically Impossible?
inferredcites →https://doi.org/10.5860/choice.27-0936openalex-snapshot
Genetic algorithms in search, optimization, and machine learning
inferredcites →https://doi.org/10.5962/bhl.title.46292openalex-snapshot
The origin of species, by Charles Darwin.
inferredcites →https://doi.org/10.5962/bhl.title.59991openalex-snapshot
On the origin of species by means of natural selection, or, The preservation of favoured races in the struggle for life /
inferredcites →https://doi.org/10.5962/bhl.title.82303openalex-snapshot
On the origin of species by means of natural selection, or, The preservation of favoured races in the struggle for life
inferredcites →https://doi.org/10.7551/mitpress/1090.001.0001openalex-snapshot
Adaptation in Natural and Artificial Systems
inferredcites →https://doi.org/10.7939/r3fb4ws2wopenalex-snapshot
Genetic algorithms for function optimization
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/0471266949.bmc141.pub2openalex-snapshot
Structure‐Based Drug Design
inferred← citeshttps://doi.org/10.1002/9780470915110.ch11openalex-snapshot
Fragment‐Based Drug Design: Considerations for Good ADME Properties
inferred← citeshttps://doi.org/10.1002/9781118742785.ch9openalex-snapshot
USING CHEMOINFORMATICS TOOLS TO ANALYZE CHEMICAL ARRAYS IN LEAD OPTIMIZATION
inferred← citeshttps://doi.org/10.1002/9781394167258.ch10openalex-snapshot
Role of Transcriptomics and Artificial Intelligence Approaches for the Selection of Bioactive Compounds
inferred← citeshttps://doi.org/10.1002/9781394249190.ch9openalex-snapshot
Scaffold Hopping andDe NovoDrug Design
inferred← citeshttps://doi.org/10.1002/9783527633326.ch17openalex-snapshot
Fragment‐Based Approaches in Virtual Screening
inferred← citeshttps://doi.org/10.1002/9783527677016.ch1openalex-snapshot
De NovoDesign: From Models to Molecules
inferred← citeshttps://doi.org/10.1002/9783527677016.ch4openalex-snapshot
Structure‐BasedDe NovoDrug Design
inferred← citeshttps://doi.org/10.1002/9783527683604.ch09openalex-snapshot
Computational Methods to Support Fragment‐based Drug Discovery
inferred← citeshttps://doi.org/10.1002/9783527836208.ch5openalex-snapshot
Computational Modeling of PROTAC Ternary Complexes and Linker Design
inferred← citeshttps://doi.org/10.1002/9783527840748.ch14openalex-snapshot
Enumerable Libraries and Accessible Chemical Space in Drug Discovery
inferred← citeshttps://doi.org/10.1002/ange.201909987openalex-snapshot
Autonome Entdeckung in den chemischen Wissenschaften, Teil I: Fortschritt
inferred← citeshttps://doi.org/10.1002/anie.201909987openalex-snapshot
Autonomous Discovery in the Chemical Sciences Part I: Progress
inferred← citeshttps://doi.org/10.1002/chin.200824206openalex-snapshot
ChemInform Abstract: Fragment‐Based de Novo Ligand Design by Multiobjective Evolutionary Optimization.
inferred← citeshttps://doi.org/10.1002/cmdc.200800355openalex-snapshot
SHOP: A Method For Structure‐Based Fragment and Scaffold Hopping
inferred← citeshttps://doi.org/10.1002/cmdc.201000085openalex-snapshot
High‐Throughput Virtual Screening Using Quantum Mechanical Probes: Discovery of Selective Kinase Inhibitors
inferred← citeshttps://doi.org/10.1002/ddr.21222openalex-snapshot
Computational Approaches for Drug Discovery
inferred← citeshttps://doi.org/10.1002/jcc.26993openalex-snapshot
A molecular evolution algorithm for ligand design in DOCK
inferred← citeshttps://doi.org/10.1002/jcc.27508openalex-snapshot
Fragment and torsion biasing algorithms for construction of small organic molecules in proteins using DOCK
inferred← citeshttps://doi.org/10.1002/med.21255openalex-snapshot
Fragment Informatics and Computational Fragment‐Based Drug Design: An Overview and Update
inferred← citeshttps://doi.org/10.1002/minf.201400056openalex-snapshot
Development of a New De Novo Design Algorithm for Exploring Chemical Space
inferred← citeshttps://doi.org/10.1002/prot.24088openalex-snapshot
Inhibition of interdomain motion in g‐actin by the natural product latrunculin: A molecular dynamics study
inferred← citeshttps://doi.org/10.1002/wcms.1226openalex-snapshot
Modeling of ribonucleic acid–ligand interactions
inferred← citeshttps://doi.org/10.1002/wcms.49openalex-snapshot
Enabling future drug discovery by de novo design
inferred← citeshttps://doi.org/10.1007/7653_2015_51openalex-snapshot
Computational Fragment-Based Drug Design
inferred← citeshttps://doi.org/10.1007/978-1-0716-0826-5_6openalex-snapshot
Computational Approaches for De Novo Drug Design: Past, Present, and Future
inferred← citeshttps://doi.org/10.1007/978-1-4939-2486-8_10openalex-snapshot
Computational Methods for Fragment-Based Ligand Design: Growing and Linking
inferred← citeshttps://doi.org/10.1007/978-1-4939-2926-9_5openalex-snapshot
Fragment-Based De Novo Design of Cyclin-Dependent Kinase 2 Inhibitors
inferred← citeshttps://doi.org/10.1007/978-1-4939-7756-7_5openalex-snapshot
De Novo Design of Ligands Using Computational Methods
inferred← citeshttps://doi.org/10.1007/978-3-031-07622-0_19openalex-snapshot
Lead Optimization in Drug Discovery
inferred← citeshttps://doi.org/10.1007/978-3-319-06508-3_1openalex-snapshot
Metaheuristics in Process Engineering: A Historical Perspective
inferred← citeshttps://doi.org/10.1007/978-981-99-6637-0_12openalex-snapshot
Recent Developments in the Application of Computer-Aided Drug Design in Neurodegenerative Disorders
inferred← citeshttps://doi.org/10.1007/s00894-012-1735-2openalex-snapshot
Computational study and peptide inhibitors design for the CDK9 – cyclin T1 complex
inferred← citeshttps://doi.org/10.1007/s10822-011-9438-9openalex-snapshot
iScreen: world’s first cloud-computing web server for virtual screening and de novo drug design based on TCM database@Taiwan
inferred← citeshttps://doi.org/10.1007/s10822-013-9687-xopenalex-snapshot
Fragment-based strategy for structural optimization in combination with 3D-QSAR
inferred← citeshttps://doi.org/10.1007/s10822-016-0008-zopenalex-snapshot
Bayesian molecular design with a chemical language model
inferred← citeshttps://doi.org/10.1016/b978-0-323-89775-4.00014-6openalex-snapshot
Molecular docking and molecular dynamics simulation
inferred← citeshttps://doi.org/10.1016/bs.arcc.2024.10.003openalex-snapshot
Toward AI/ML-assisted discovery of transition metal complexes
inferred← citeshttps://doi.org/10.1016/j.abb.2020.108730openalex-snapshot
Artificial intelligence in the early stages of drug discovery
inferred← citeshttps://doi.org/10.1016/j.asoc.2014.09.042openalex-snapshot
Evolutionary algorithms for de novo drug design – A survey
inferred← citeshttps://doi.org/10.1016/j.bbagen.2020.129519openalex-snapshot
Identification and characterization of fragment binding sites for allosteric ligand design using the site identification by ligand competitive saturation hotspots approach (SILCS-Hotspots)
inferred← citeshttps://doi.org/10.1016/j.bmc.2008.06.036openalex-snapshot
Novel inhibitors of anthrax edema factor
inferred← citeshttps://doi.org/10.1016/j.bmcl.2018.06.046openalex-snapshot
Recent applications of machine learning in medicinal chemistry
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2023.107691openalex-snapshot
STAGAN: An approach for improve the stability of molecular graph generation based on generative adversarial networks
inferred← citeshttps://doi.org/10.1016/j.drudis.2010.04.003openalex-snapshot
Evolving molecules using multi-objective optimization: applying to ADME/Tox
inferred← citeshttps://doi.org/10.1016/j.drudis.2011.05.005openalex-snapshot
A molecular informatics view on best practice in multi-parameter compound optimization
inferred← citeshttps://doi.org/10.1016/j.drudis.2022.103439openalex-snapshot
Docking-based generative approaches in the search for new drug candidates
inferred← citeshttps://doi.org/10.1016/j.ejmech.2018.07.042openalex-snapshot
In silico fragment-based drug design with SEED
inferred← citeshttps://doi.org/10.1016/j.ejmech.2020.112316openalex-snapshot
Substituted oxindol-3-ylidenes as AMP-activated protein kinase (AMPK) inhibitors
inferred← citeshttps://doi.org/10.1016/j.ejmech.2020.112572openalex-snapshot
Automated design and optimization of multitarget schizophrenia drug candidates by deep learning
inferred← citeshttps://doi.org/10.1016/j.ejmech.2026.118997openalex-snapshot
From fragments to drugs: How AI and in silico methods accelerate fragment-to-lead optimization
inferred← citeshttps://doi.org/10.1016/j.ijggc.2016.02.023openalex-snapshot
Computer-aided molecular design of imidazole-based absorbents for CO 2 capture
inferred← citeshttps://doi.org/10.1016/j.tibtech.2008.09.005openalex-snapshot
Voyages to the (un)known: adaptive design of bioactive compounds
inferred← citeshttps://doi.org/10.1017/s0033583512000108openalex-snapshot
Biophysical and computational fragment-based approaches to targeting protein–protein interactions: applications in structure-guided drug discovery
inferred← citeshttps://doi.org/10.1021/acs.chemrev.8b00728openalex-snapshot
Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery
inferred← citeshttps://doi.org/10.1021/acs.jcim.1c00608openalex-snapshot
Kinase Inhibitor Scaffold Hopping with Deep Learning Approaches
inferred← citeshttps://doi.org/10.1021/acs.jcim.1c01156openalex-snapshot
CHARMM-GUI Ligand Designer for Template-Based Virtual Ligand Design in a Binding Site
inferred← citeshttps://doi.org/10.1021/acs.jcim.3c00209openalex-snapshot
BMaps: A Web Application for Fragment-Based Drug Design and Compound Binding Evaluation
inferred← citeshttps://doi.org/10.1021/acs.jcim.4c00234openalex-snapshot
Streamlining Computational Fragment-Based Drug Discovery through Evolutionary Optimization Informed by Ligand-Based Virtual Prescreening
inferred← citeshttps://doi.org/10.1021/acs.jcim.5c01225openalex-snapshot
FragOPT: An ML-Driven Computational Workflow for Rational Fragments Optimization Toward Lead Compounds
inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00038openalex-snapshot
Chemical-Space-Based de Novo Design Method To Generate Drug-Like Molecules
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00478openalex-snapshot
New Data Structure for Computational Molecular Design with Atomic or Fragment Resolution
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b01120openalex-snapshot
Deep Generative Models for 3D Linker Design
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.7b01558openalex-snapshot
Binding-Site Compatible Fragment Growing Applied to the Design of β2-Adrenergic Receptor Ligands
inferred← citeshttps://doi.org/10.1021/bk-2011-1076.ch001openalex-snapshot
Overview: Fragment-Based Drug Design
inferred← citeshttps://doi.org/10.1021/ci100080ropenalex-snapshot
NovoFLAP: A Ligand-Based De Novo Design Approach for the Generation of Medicinally Relevant Ideas
inferred← citeshttps://doi.org/10.1021/ci100340wopenalex-snapshot
Sequence, Structure, and Active Site Analyses of p38 MAP Kinase: Exploiting DFG-out Conformation as a Strategy to Design New Type II Leads
inferred← citeshttps://doi.org/10.1021/ci100462topenalex-snapshot
Reproducing Crystal Binding Modes of Ligand Functional Groups Using Site-Identification by Ligand Competitive Saturation (SILCS) Simulations
inferred← citeshttps://doi.org/10.1021/ci200136jopenalex-snapshot
Structure-Based Fragment Hopping for Lead Optimization Using Predocked Fragment Database
inferred← citeshttps://doi.org/10.1021/ci4000163openalex-snapshot
In Silico Fragment-Based Drug Discovery: Setup and Validation of a Fragment-to-Lead Computational Protocol Using S4MPLE
inferred← citeshttps://doi.org/10.1021/ci400043qopenalex-snapshot
Design of Linear Ligands for Selective Separation Using a Genetic Algorithm Applied to Molecular Architecture
inferred← citeshttps://doi.org/10.1021/ci400078gopenalex-snapshot
LiGen: A High Performance Workflow for Chemistry Driven de Novo Design
inferred← citeshttps://doi.org/10.1021/ci400418copenalex-snapshot
De Novo Design of Drug-Like Molecules by a Fragment-Based Molecular Evolutionary Approach
inferred← citeshttps://doi.org/10.1021/ci400474uopenalex-snapshot
LIBSA – A Method for the Determination of Ligand-Binding Preference to Allosteric Sites on Receptor Ensembles
inferred← citeshttps://doi.org/10.1021/ci400731wopenalex-snapshot
Fragment-Based Lead Discovery and Design
inferred← citeshttps://doi.org/10.1021/ci4007497openalex-snapshot
Automated Design of Realistic Organometallic Molecules from Fragments
inferred← citeshttps://doi.org/10.1021/ci5006355openalex-snapshot
Evaluation of a Semi-Automated Workflow for Fragment Growing
inferred← citeshttps://doi.org/10.1021/ci9000647openalex-snapshot
A Novel In Silico Approach to Drug Discovery via Computational Intelligence
inferred← citeshttps://doi.org/10.1021/ci9002409openalex-snapshot
Improving Quantitative Structure−Activity Relationships through Multiobjective Optimization
inferred← citeshttps://doi.org/10.1021/ci9003305openalex-snapshot
GARLig: A Fully Automated Tool for Subset Selection of Large Fragment Spaces via a Self-Adaptive Genetic Algorithm
inferred← citeshttps://doi.org/10.1021/ct300088ropenalex-snapshot
Site-Specific Fragment Identification Guided by Single-Step Free Energy Perturbation Calculations
inferred← citeshttps://doi.org/10.1021/ja300865uopenalex-snapshot
An Evolutionary Algorithm for de Novo Optimization of Functional Transition Metal Compounds
inferred← citeshttps://doi.org/10.1038/nature11691openalex-snapshot
Automated design of ligands to polypharmacological profiles
inferred← citeshttps://doi.org/10.1038/s41598-020-78537-2openalex-snapshot
Autonomous molecule generation using reinforcement learning and docking to develop potential novel inhibitors
inferred← citeshttps://doi.org/10.1038/s41598-025-12685-1openalex-snapshot
STELLA provides a drug design framework enabling extensive fragment-level chemical space exploration and balanced multi-parameter optimization
inferred← citeshttps://doi.org/10.1038/s42256-023-00636-2openalex-snapshot
Testing the limits of SMILES-based de novo molecular generation with curriculum and deep reinforcement learning
inferred← citeshttps://doi.org/10.1039/c0md00020eopenalex-snapshot
Chemical space as a source for new drugs
inferred← citeshttps://doi.org/10.1039/c5ra22800jopenalex-snapshot
TD-DFT based fine-tuning of molecular excitation energies using evolutionary algorithms
inferred← citeshttps://doi.org/10.1039/c9sc01928fopenalex-snapshot
Efficient multi-objective molecular optimization in a continuous latent space
inferred← citeshttps://doi.org/10.1039/d4sc02934hopenalex-snapshot
Augmenting genetic algorithms with machine learning for inverse molecular design
inferred← citeshttps://doi.org/10.1039/d5dd00464kopenalex-snapshot
A simple compound prioritization method for drug discovery considering multi-target binding
inferred← citeshttps://doi.org/10.1042/ebc20200011openalex-snapshot
Targeting RNA structures in diseases with small molecules
inferred← citeshttps://doi.org/10.1073/pnas.1705381114openalex-snapshot
Structure-based prediction of ligand–protein interactions on a genome-wide scale
inferred← citeshttps://doi.org/10.1080/17460441.2017.1280024openalex-snapshot
Computational polypharmacology: a new paradigm for drug discovery
inferred← citeshttps://doi.org/10.1080/17460441.2019.1615435openalex-snapshot
Approaching Target Selectivity by De Novo Drug Design
inferred← citeshttps://doi.org/10.1080/17460441.2020.1767063openalex-snapshot
An up-to-date overview of computational polypharmacology in modern drug discovery
inferred← citeshttps://doi.org/10.1080/17460441.2023.2234285openalex-snapshot
Linkers in fragment-based drug design: an overview of the literature
inferred← citeshttps://doi.org/10.1093/bib/bbab544openalex-snapshot
Comprehensive assessment of deep generative architectures for de novo drug design
inferred← citeshttps://doi.org/10.1101/2022.07.15.500218openalex-snapshot
Testing the Limits of SMILES-based De Novo Molecular Generation with Curriculum and Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/cec.2010.5586531openalex-snapshot
A Bayesian Optimization Algorithm for De Novo ligand design based docking running over GPU
inferred← citeshttps://doi.org/10.1109/tcbb.2012.35openalex-snapshot
De Novo Design of Potential RecA Inhibitors Using MultiObjective Optimization
inferred← citeshttps://doi.org/10.1109/tevc.2024.3382145openalex-snapshot
A Survey on Evolutionary Computation-Based Drug Discovery
inferred← citeshttps://doi.org/10.1111/cbdd.13030openalex-snapshot
Fragment‐based drug discovery as alternative strategy to the drug development for neglected diseases
inferred← citeshttps://doi.org/10.1111/j.1582-4934.2008.00665.xopenalex-snapshot
Docking, virtual high throughput screening and in silico fragment‐based drug design
inferred← citeshttps://doi.org/10.1111/j.1747-0285.2008.00672.xopenalex-snapshot
Concept of Combinatorial De Novo Design of Drug‐like Molecules by Particle Swarm Optimization
inferred← citeshttps://doi.org/10.1146/annurev-matsci-070214-020823openalex-snapshot
What Is High-Throughput Virtual Screening? A Perspective from Organic Materials Discovery
inferred← citeshttps://doi.org/10.1186/s13321-018-0287-6openalex-snapshot
Multi-objective de novo drug design with conditional graph generative model
inferred← citeshttps://doi.org/10.1186/s13321-020-00429-4openalex-snapshot
AutoGrow4: an open-source genetic algorithm for de novo drug design and lead optimization
inferred← citeshttps://doi.org/10.1186/s13321-022-00582-yopenalex-snapshot
LEADD: Lamarckian evolutionary algorithm for de novo drug design
inferred← citeshttps://doi.org/10.1186/s13321-025-00946-0openalex-snapshot
Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology
inferred← citeshttps://doi.org/10.1517/17460441.2010.497534openalex-snapshot
De novodesign: balancing novelty and confined chemical space
inferred← citeshttps://doi.org/10.1517/17460441.2011.554394openalex-snapshot
The quest for novel chemical matter and the contribution of computer-aidedde novodesign
inferred← citeshttps://doi.org/10.1517/17460441.2011.588696openalex-snapshot
Strategies of multi-objective optimization in drug discovery and development
inferred← citeshttps://doi.org/10.2174/092986712803530467openalex-snapshot
Fragment Based Drug Design: From Experimental to Computational Approaches
inferred← citeshttps://doi.org/10.2174/138161212799436386openalex-snapshot
From Laptop to Benchtop to Bedside: Structure-based Drug Design on Protein Targets
inferred← citeshttps://doi.org/10.2174/138620712799361825openalex-snapshot
Computer-Aided Drug Design: Lead Discovery and Optimization
inferred← citeshttps://doi.org/10.2174/138955712802762284openalex-snapshot
Multi-Objective Optimization Methods in De Novo Drug Design
inferred← citeshttps://doi.org/10.2174/156802610790232305openalex-snapshot
Computational Approaches for Fragment-Based and De Novo Design
inferred← citeshttps://doi.org/10.2174/1568026614666140929115506openalex-snapshot
Revisiting De Novo Drug Design: Receptor Based Pharmacophore Screening
inferred← citeshttps://doi.org/10.2174/1568026623666221017143244openalex-snapshot
Artificial Intelligence in De novo Drug Design: Are We Still There?
inferred← citeshttps://doi.org/10.2174/9789815179934123010008openalex-snapshot
FBDD & De Novo Drug Design
inferred← citeshttps://doi.org/10.2298/bg20131217randjelovicopenalex-snapshot
Design of peptide and small molecule inhibitors of cyclin dependent kinase 9/cyclin T1 protein-protein interaction using computational methods
inferred← citeshttps://doi.org/10.26434/chemrxiv-2023-q0zdfopenalex-snapshot
Multi-Objective and Many-Objective Optimisation: Present and Future in de novo Drug Design
inferred← citeshttps://doi.org/10.26434/chemrxiv-2023-q0zdf-v2openalex-snapshot
Multi- and Many-Objective Optimisation: Present and Future in de novo Drug Design
inferred← citeshttps://doi.org/10.3389/fchem.2020.00093openalex-snapshot
In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery
inferred← citeshttps://doi.org/10.3389/fchem.2023.1288626openalex-snapshot
Multi-and many-objective optimization: present and future in de novo drug design
inferred← citeshttps://doi.org/10.3389/fmolb.2022.834453openalex-snapshot
Fragment-Based Drug Discovery by NMR. Where Are the Successes and Where can It Be Improved?
inferred← citeshttps://doi.org/10.3389/fphar.2021.719694openalex-snapshot
Update and New Insights on Future Cancer Drug Candidates From Plant-Based Alkaloids
inferred← citeshttps://doi.org/10.3390/ijms22041676openalex-snapshot
Advances in De Novo Drug Design: From Conventional to Machine Learning Methods
inferred← citeshttps://doi.org/10.3390/molecules181113487openalex-snapshot
Template-Based de Novo Design for Type II Kinase Inhibitors and Its Extended Application to Acetylcholinesterase Inhibitors
inferred← citeshttps://doi.org/10.3390/ph19020308openalex-snapshot
Frags2Drugs: A Novel In Silico Fragment-Based Approach to the Discovery of Kinase Inhibitors
inferred← citeshttps://doi.org/10.48550/arxiv.1801.07299openalex-snapshot
Multi-Objective De Novo Drug Design with Conditional Graph Generative Model
inferred← citeshttps://doi.org/10.5423/ppj.rw.04.2017.0084openalex-snapshot
Computer-Aided Drug Discovery in Plant Pathology
inferred← citeshttps://doi.org/10.6084/m9.figshare.18482568openalex-snapshot
Additional file 1 of LEADD: Lamarckian evolutionary algorithm for de novo drug design
inferred← citeshttps://doi.org/10.70675/1a4f06f0zdfa4z41efza87az70239c45c50copenalex-snapshot
Conception d'un logiciel pour la recherche de nouvelles molécules bioactives
inferred← citeshttps://doi.org/10.70675/c04eeb3az351fz48ddza731z6ad3d5044e23openalex-snapshot
Développement d'outils de chémoinformatique pour l'identification d'inhibiteurs de protéines kinases à partir de fragments
inferred← citeshttps://doi.org/10.70675/d040b5b4zd926z4f6ez9870z7af586f801abopenalex-snapshot
Deep generative neural networks for novelty generation : a foundational framework, metrics and experiments
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.